AWS Big Data
OCTOBER 3, 2023
A data lake is a centralized repository that you can use to store all your structured and unstructured data at any scale. You can store your data as-is, without having to first structure the data and then run different types of analytics for better business insights. On the navigation pane, select Crawlers.
Ontotext
DECEMBER 1, 2023
Atanas Kiryakov presenting at KGF 2023 about Where Shall and Enterprise Start their Knowledge Graph Journey Only data integration through semantic metadata can drive business efficiency as “it’s the glue that turns knowledge graphs into hubs of metadata and content”.
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AWS Big Data
MARCH 7, 2024
You can take all your data from various silos, aggregate that data in your data lake, and perform analytics and machine learning (ML) directly on top of that data. You can also store other data in purpose-built data stores to analyze and get fast insights from both structured and unstructured data.
Ontotext
NOVEMBER 22, 2020
Content Enrichment and Metadata Management. The value of metadata for content providers is well-established. When that metadata is connected within a knowledge graph, a powerful mechanism for content enrichment is unlocked. Ontotext Platform can be employed for a number of applications within an enterprise.
Cloudera
JUNE 25, 2021
Using easy-to-define policies, Replication Manager solves one of the biggest barriers for the customers in their cloud adoption journey by allowing them to move both tables/structured data and files/unstructured data to the CDP cloud of their choice easily. Understanding the data sets to be replicated from the CDH Cluster.
Cloudera
SEPTEMBER 1, 2020
DDE also makes it much easier for application developers or data workers to self-service and get started with building insight applications or exploration services based on text or other unstructured data (i.e. data best served through Apache Solr). Coordinates distribution of data and metadata, also known as shards.
AWS Big Data
MARCH 10, 2023
Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.
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